{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Parte 6\n",
    "\n",
    "Algoritmo FFT, Fast Fourier ransform e sue applicazioni nell'elaborazione di segnali e immagini."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Funzione box\n",
    "\n",
    "Teoria dei segnali,\n",
    "\n",
    "     f = box(t, A,  B)\n",
    "\n",
    "A e B sono gli estremi in cui box è non nulla."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "function f = boxf(t, a, b)\n",
    "\n",
    "f = zeros(size(t));\n",
    "% si estraggono i valori di t in [A,B]\n",
    "indici = t >= a & t <= b; \n",
    "\n",
    "% si impone che la funzione abbia valore unitario\n",
    "f(indici) = 1;\n",
    "\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Esercizio 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dt = 0.01; % pass di campionamento nel dominio reale (distanza tra due campioni)\n",
    "t = 0.01; % pass di campionamento nel dominio reale (distanza tra due campioni)\n",
    "fs = 1/dt; % frequenza di campionamento (numero di campioni raccolti al secondo) [Hz]\n",
    "\n",
    "durata_segnale = 4;\n",
    "durata_box = 0.05; % regola dilatazione e restingimento\n",
    "t = (0:dt:durata_segnale); % campionamento\n",
    "\n",
    "a = 0; b = durata_box;\n",
    "f_box = boxf(t, a, b);\n",
    "N = length(t);\n",
    "\n",
    "figure\n",
    "plot(t, f_box, 'r');\n",
    "title('Box');\n",
    "box off;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "% Trasformata di Fourier discreta con shift di frequenza\n",
    "% gli elementi dell'array a frequenza zero sono posti al centro dell'array\n",
    "tr = fftshift(fft(f_box));\n",
    "\n",
    "delta_u = 1 / (N * dt);\n",
    "u = (- fs / 2 : delta_u : fs / 2 - delta_u);\n",
    "\n",
    "figure\n",
    "plot(u, abs(tr)) % abs di un numero complesso dà il modulo del numero complesso\n",
    "title(\"Trasformata di Fourier\");\n",
    "box off"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "L'alterazione della durata della box permette di dimostrare intuitivamente la scalatura del dominio reale."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Esercizio 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "clearvars\n",
    "close all\n",
    "\n",
    "fs = 350; % frequenza di campionamento (numero di campioni raccolti al secondo) [Hz]\n",
    "dt = 1/fs; % pass di campionamento nel dominio reale (distanza tra due campioni)\n",
    "durata_segnale = 4;\n",
    "t = (0:dt:durata_segnale); % campionamento\n",
    "N = length(t);\n",
    "\n",
    "% funzione generatrice del primo segnale\n",
    "f_box = 2 * sin(2 * pi * 15 * t) + 3 * sin(2 * pi * 60 * t);\n",
    "\n",
    "% funzione generatrice del segnale perturbato\n",
    "fbox_p = f_box + 0.5 * sin(2 * pi * 150 * t);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure\n",
    "plot(t, f_box, 'r');\n",
    "title(\"Funzione sinusoidale\");\n",
    "box off"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure\n",
    "plot(t, fbox_p, 'r');\n",
    "title(\"Funzione sinusoidale perturbata\");\n",
    "box off"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "% calcolo della trasformata di Fourier\n",
    "tr = fftshift(fft(f_box));\n",
    "tr_p = fftshift(fft(fbox_p));\n",
    "\n",
    "% Passaggio al dominio delle frequenze\n",
    "delta_u = 1 / (N * dt); % passo di campionamento nel dominio di Fourier\n",
    "u = (-fs/2:delta_u:fs/2- delta_u); %costruzione vettore delle frequenze"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure\n",
    "% abs di un numero complesso dà il modulo del numero complesso\n",
    "stem(u, abs(tr));\n",
    "title(\"Spettro delle frequenze\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lo spettro delle frequenze perturbato mostra la presenza di una frequenza a 150 Hz che non dovrebbe essere presente. Si opera una ripulitura del segnale."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "% si annullano le frequenze che risultano in modulo maggiori di ftaglio\n",
    "ftaglio = 70;\n",
    "f_box_denoise = (abs(u) <= ftaglio).* fbox_p; "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure; \n",
    "stem(u, abs(f_box_denoise));\n",
    "title(\"Spettro delle frequenze ripulito\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "% verifica della corretta ricostruzione della funzione generatrice\n",
    "ricostr = ifft(ifftshift(f_box_denoise));\n",
    "\n",
    "figure; \n",
    "plot(t, real(ricostr));\n",
    "title(\"Funzione generatrice ottenuta dal segnale ripulito\");\n",
    "box off"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Esercizio 3\n",
    "\n",
    "A partire dal file audio `obo-c.wav` fornito, si aggiunga al segnale una frequenza di disturbo tramite una funzione sinusoidale di ampiezza 0.05 e frequenza 7500 Hz. Si effettui la ripulitura del segnale tramite un apposito filtro di Fourier di dimensione adeguata."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sampling frequency:\t 44100.00 Hz\n",
      "signal length: \t\t 1.697959 s\n"
     ]
    }
   ],
   "source": [
    "clearvars\n",
    "\n",
    "% restituisce una matrice di uint8 e la frequenza di campionamento\n",
    "[f, fs] = audioread(\"resources/obo-c.wav\"); \n",
    "fprintf(\"sampling frequency:\\t %.2f Hz\\n\", fs);\n",
    "\n",
    "% numero campioni totale\n",
    "num_samp = length(f);\n",
    "durata = num_samp / fs;\n",
    "fprintf(\"signal length: \\t\\t %f s\\n\", durata);\n",
    "\n",
    "% passo di campionamento (periodo T)\n",
    "period = 1 / fs;\n",
    "xx = 0 : period : durata - period;\n",
    "\n",
    "% frequenza di disturbo\n",
    "fp = f + 0.05 * sin(2 * pi * 7500 * xx');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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SIlTAUASJsdxcHU0CBidIjG6Q3lTWf5ElYBCCxIiGyowsAbcSJEYxWl00CbiBIAEQBEFiaOMMdLx3B/QjSGRAk4CrBIlsaBJwiSAxHCEBEiJIAARBkMiMExyAXoLEEHLaj5zONpSNIJGx5GrROwKLL8TXGJlBmASJQeVoJ341RdGV+c/R04GSECSyN8E2GP1AfgkSAwl/Lz9CisJ/UlAqgkSpaRKEQ5AIwphh0BUoAEGi7MQMAiFI3C6dXXaGYdAkCIEgARAEQSL3jG+gGASpsPL4HzkjzPCknmPulhUUjyAVzaWPxhl/P1uePXV5nimESZAKxS4VyC9BKr5xKpV+4YZ6xInPnqJDhgSpFOxngfAJUkHk8RSGfgZ8Igk938IsRsgdQSqLfO1nb53bfD0dYBCCVATGCpNV2icO2RKkfBvqnbrC7GdTeCKFWVaQI4KUY8XeafZ7dsV+1lBmgpQ/l/71ddj7TvyWyYnnIYQ5AVIgSAStt0Ypn0kohJAyQcqHCX4UUB4V6aR2oJ+vsp4BbjHxFFXWf+nsPhjwQQFSY4QEfQkzpMkIKVCJ7grjid86TgJIkxFSWNI8r8x51amxSGEQghQcO6+gjPlydE/H8LLCrQQpICHss0KYh8K4tDAtW7iZY0ihyGRvdelgkj1m0i6d4ti7wB3SA0EKQrYliPeSatTPICfKX3uvoa4HBAmC0A2VoRKl5RhS9kL4kzmEeSiSfH1tPARCkOB2Q0Vi/KJoEuUkSBmz6+FaVgxKSJAgUJpE2QhSluxxcmTAF8trCiMrSJDyuBfI4zyTMisJpVKEINloKTCrN+VRhCDFbLck7dZ1zEoI48h9kPK4C/D9pwzF2kJJ5D5IvXKx3eZiJunnhpcvha+wgmIrVJCC1f0CAruVAvAiQkIEacLi6lwtkL0YY7IKUXhFC1I4G60UFdjV1zTbL/mFYsh3kELbPkObH5LT+weH1x0mIt9BulZWewd7pRLyosMEFTBImbBjKqEMv+QXCqmYQUp5o7WPABhfMYOUGscPSJ9VjqIqbJBS2GjtFwAmqLBBGsoNA53ufxRFCkQwrIoUUqXT6aT/qLOzs58/fx5/Ordulp3dB+NPBAI0yLoNWRltJ1/2EZIaAQSi4EG6+aQDNQIIR46DNHhOrr2lGpFrVmCKJ8dBGsqlrdfGTAFYjSmYsgQp8j9DFJFVmiIZN0jNZvPi4mIis5IOWaJgrM8Uxlfj3Hl5eblarZ6enq6vry8uLnavv3//fq1Wi6KoVqttbGyMO4/AjeImORGcvBs9SIeHh9Vq9dWrV+12e2trqxukdrtdq9XevXs3mRkEBnNpqNTZfVBZ/0WlyJHR37JrNptzc3NRFFWr1ZOTk+717XZ7ampqa2trZ2cnX+/mQZH4eBFyZ6xjSNVqNb6wsLDQvfLi4uLOnTv1en16enptba3ffSs9xpkH4GaaRAoqfzTaRMYKUrvdji/0jpDq9frGxsbi4uLKysp///vffvft9BhnHoBbaRJJ6/zRaBMZPUhzc3O//fZb9PtBo+71+/v7jUZj5MkCSXB+KeEbPUj1ev3k5GRnZ2dtbW1lZSWKokajMTs7u7CwEB9AWl5efv78+eRmFRiXJhGycT/tu9FoVKvV7sGkW6+PTeTTvm1aMBqn3pG0bD7te3Fx8drq9LseyJw/5ghTiT46COjSJAIkSFBSmkRoBAnKS5MIiiABEARBAiAIggSl5l07wiFIUHaaRCAECYAgCBIAQchrkLzJABNkgyIEeQ0SMFmaROYECYAgCBLw/xkkkS1BAiAIggRAEAQJgCAIEgBBECTgf5zXQIYECYAgCBLwBwZJZEWQAAiCIAGXGSSRCUECIAiCBFzDIIn0CRIAQRAk4HoGSaRMkAAIgiABfRkkkSZBAiAIggTcxCCJ1AgSAEHIZZD8yQZpssWRjlwGCUiZJpECQQIgCIIEDMQgiaQJEgBBECRgUAZJJEqQgCFoEskRJACCIEjAcCrrvxgnkQRBAkahSUycIAEQBEECRmSQxGQJEjA6TWKCBAkYi3McmBRBAiZAkxifIAGToUmMSZCAidEkxiFIwCRpEiPLX5Cs7hA4pzkwmvwFCcgFTWJYggQkRZMYiiABCdIkBidIAARBkIBkGSQxIEECEqdJDEKQgDRoErcSJCAlmsTNBAlIjyZxA0ECUqVJ9CNIQNo0iWsJEpABTeKqnAXJSgxQVDkLElAY/r7kEkECMqNJ9BIkIEuaRJcgARnTJGKCBGRPk4gECQiELz4nT0GyskLh2czLLE9BAsrAUKm0BAmAIAgSECKDpBLKTZCsnVA2tvqyyU2QgBJyPKlU8hEkaySUmT1ASeQjSEDJaVIZCBKQD5pUeIIE5IYmFVsOgmQVBLqc5lBgOQgSAGUgSED+GCcVUlJBajabFxcXCU0cIPJ+fuEkEqTl5eWff/75xYsXjUYjiekDxAyViuSriU/x8PCwWq2+evWq3W5vbW0tLi5O/CEAenWb1Nl9kO2cMI7JB6nZbM7NzUVRVK1WT05Oxpyav32AwfXuMcQpdyYfpCiKqtVqfGFhYaHfbZQGSFTIO5nixbJSqfT+ePfu3REmkkiQ2u12fOGGEdKAr0fIqxQQpuLt7sPX6XR6f5ydnR1hIpMP0tzcXLPZjKKo3W7XarUxp9bZfaBJwM0UqBgmH6R6vb6/v7+zs3NycrKysjL+BDUJuEqEiieRt+w+fPjQaDT++te/dg8mAUyEDhVYIkGKosjZ3sAE6VAZJBUkgPHpUKkIEhAiKSohQQICokNlJkhA9nSIKC9BildWJ39D8UgRXfkIElA8UsQlefqCPqsvFENn94HNmauMkID06BA3ECQgDVLErQQJSJYUMaCcBckHrUJe6BDDylmQgJCJEOMQJGBcOsRECBIwIh1isgQJGJoUkYQ8/WMsEAI1IiFGSMCgpIhEGSEBA1EjkiZIwO3UiBTkL0g2DEiZjY505C9IQJrUiNQIEtCXGpEmQQKup0akTJCAa6gR6RMkAIIgSMBlhkdkQpCAP1AjsiJIwP+oERnKZZBsM5AEWxbZymWQgIlTIzInSAAEQZAAwyOCIEhQdmpEIAQJSk2NCEfBvzG2d2OrrP+S4ZxAaKSI0BR5hHRpe+vsPrAFUnLxJmBbIEwFHyFd1dl9YKhEqVz9yyyrOYGbFXaElOhWZ5MmF4yEyJdKp9NJ/1FnZ2c/f/485kRuGOjcuhGOMEiKh1ZXp2y8RSC6K+e1KyqkabSdfAFHSINsiqNtrtfeyx+hhKB3JbRCklOlO4Y0lME3bIemyJACUQwFHCEN6OZteIRxj6ESmbDWURhGSNcYZwuP72u0RAqkiIIpWpCG2kSvfZ9tIht5d8r+M5ckSBGFVLQgDetSkya4nV+dlDgxEWpEUZX3GFJXJv+7bp8CcEmhRkgj7+XlgVywolJsRkiZsXNhKFYYCk+QIAfUiDIQpCzZyzAI6wklIUgZs6/hZtYQyqM4QcrvdpvfOSdRPvuDsinUWXaQF72fzH3zDaA8BCkIPps1F66NxLAv3LVflxd/YcTVT/eAUinI9yEVYxvu3R8N8plGvXsxkjaRL9kqxooKtxptJ5/jIEV/3IMX0oDftKZJSRtwHbv1hSjwugq9fEFfAdl/hWCor8W64cZeTbiZIBWBPV1yRli2V48SOV8OBuGkhoLwPUxJ8OmIkKZ8j5D84Tk+C7AfSwZSZoRUKEOddOdbBPuRIshEvkdIXDXgzrT7LVCj3b2ojLkhQ0ZIpXPrDvfWDxEoJB2CzBkhFZAzj4dlsUAIBKmYrt3DDrvbLcn7V2V4jpALglRY3f3smP8HU+z9dbGfHeSLY0hFZm8L5IgRErcrZNhK8oYk5IggARAEQWIggQwmJjUbgTwdoJcgMaiUd+K9/7rbe17G+J9VqkYQpnx/HxLpS/q/ZYeqxbCfkyRFkI7RdvLOsiMUY37RQ7849Z7+PtqMAenwlh3DGef/mW54q238WlwNj/PoIF+8ZccoBnyv7NY3yryNBoXkK8wJS78PFL96G4DIMSRGc+sngisNMCwjJMZy7SkDagSMwAiJcUkRMBFGSEyMGgHjECQAgiBIAARh3CA1m82Li4uJzAoAZTbWSQ3Ly8vVavX09HR9fX1xcbF7/f3792u1WhRFtVptY2Nj3HkEoARGD9Lh4WG1Wn316lW73d7a2uoGqd1u12q1d+/eTWYGASiH0YPUbDbn5uaiKKpWqycnJ93r2+321NTU1tbW119/vbq6OjU1NYHZBKDoxjqGVK1W4wsLCwvdKy8uLu7cuVOv16enp9fW1vrdt9JjnHkAIHOVPxptIkOPkBqNxq+//vrNN99EUdRut+Mre0dI9Xq9Xq9HUbS4uHh4eNhvOpl8qCsASbi0S5+dnR1hIkMHaXFxMT5cdHh42Gw2o98PGnVvsL+/X6vVes9xAIBbjX4MqV6v7+/v7+zsnJycrKysRFHUaDRevHjx97//fW1t7dGjR6enp8+fP5/crAJQZON+H1Kj0ahWq92DSbdeH/N9SAAFls1XmPd7a85bdgAMxUcHARAEQQIgCIIEQBAECYAgCBIAQRAkAIIgSAAEQZAACIIgARAEQQIgCIIEQBAECYAgCBIAQRAkAIIgSAAEQZAACIIgARAEQQIgCIIEQBAECYAgCBIAQRAkAIIgSAAEQZAACIIgARAEQQIgCIIEQBAECYAgCBIAQRAkAIIgSAAEQZAACIIgARAEQQIgCIIEQBAECYAgCBIAQRAkAIIgSAAEQZAACIIgARAEQQIgCIIEQBAECYAgCBIAQRAkAIIgSAAEQZAACIIgARAEQQIgCIIEQBAECYAgCBIAQRAkAIIgSAAEQZAACIIgARAEQQIgCIIEQBAECYAgCBIAQRAkAIIgSAAEQZAACIIgARAEQQIgCIIEQBAECYAgCBIAQRAkAIIgSAAEQZAACIIgARAEQQIgCIIEQBAECYAgCBIAQRAkAIIgSAAEQZAACIIgARAEQQIgCEkF6eLiot1uJzRxRlOpVLKehZKy5LNiyWdi5MWeVJAODg5++umnhCYOQPEkEqTHjx/v7u4mMWUAiiqRIH348OH7779PYsoAFNVXWT3w7OxsVg9dWnfv3rXYM2HJZ8WSz8Tdu3dHu+PEgtRoNH799ddvvvnm+fPnt974X//6V++PnU5nUrPBDSqVikWdCUs+K5Z8ai6dyDDaYp9YkBYXFxcXFwe8sVUkExZ7Viz5rFjyqZnIovZ/SAAEwXgWgCAYIQEQhAyC1Gw2Ly4u0n/ccrK0Q+CDS1JjUYeg2WyO9iqkfdr38vJytVo9PT1dX18f/CQIRtNvad+/f79Wq0VRVKvVNjY2spvBsjg4OPjPf/5jUaeg36K2zqfj4uLixYsXtVqt3W6PsKhTDdLh4WG1Wn316lW73d7a2hKkRPVb2vGK8u7du0znrkQeP358enrqX8VT0G9RW+dTc3BwsLCwEHfo4cOHQQep2WzOzc1FUVStVk9OTtJ86BLqt7Tb7fbU1NTW1tbXX3+9uro6NTWV3TyWwocPH3Z2drKei1Lot6it86l59OhRfGG0IwVpH0OqVqvxhYWFhZQfuoSuXdoXFxd37typ1+vT09Nra2sZzRqkxzqfmmq1Wq1WG43GixcvVldXh7172seQuke6jJBScO3Srtfr9Xo9iqLFxcXDw8Ns5gxSZJ1P087Ozr///e+//e1v3T+IB5fqCGlubu63336Lfn9LN82HLqF+S3t/f7/RaGQ3X5A263xqfv7555FrFKU8QqrX6/v7+zs7OycnJysrK2k+dAldWtrxIPrz588LCwtra2uPHj06PT0d5IMHIaes8+mLT/heXl6Ofxz2RJIMPqmh0WjE7zOm/Ljl1G9pexUoG+t8+Hx0EABB8NFBAARBkAAIgiABEARBAiAIggRAEP4Ptg36Z2pUDKUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure\n",
    "plot(xx, f);\n",
    "title(\"Segnale esatto\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure\n",
    "plot(xx, fp);\n",
    "title(\"Segnale perturbato\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "% Ricostruzione del segnale audio tramite filtro di Fourier\n",
    "\n",
    "%{\n",
    "1. Si calcola la trasformata di Fourier con shift del dominio\n",
    "delle frequenze. La frequenza 0-esima al centro.\n",
    "%}\n",
    "tr_fourier = fftshift(fft(fp));\n",
    "\n",
    "%{\n",
    "2. Determinazione della frequenza di campionamento nel dominio di Fourier.\n",
    "\n",
    "Per il teorema di Nyquist la frequenza di campionamento nel dominio\n",
    "di Fourier deve essere il doppio della frequenza di campionamento nel\n",
    "dominio reale. Perciò il range di frequenze è [-fs/2, +fs/2].\n",
    "%}\n",
    "samp_freq = fs / num_samp;\n",
    "xx_freq = (-fs/2 : samp_freq : fs/2 - samp_freq)';\n",
    "\n",
    "%{\n",
    "3. Ricostruzione del segnale con applicazione di un filtro passa basso\n",
    "Si annullano nella trasformata di Fourier dell'immagine tutte le frequenze che\n",
    "stanno fuori dal vettore delle frequenze non filtrate, facendo una moltiplicazione \n",
    "point-wise tra i valori della trasformata di Fourier ed il filtro_PB;\n",
    "%}\n",
    "\n",
    "%{ il filtro non può essere definito in questo modo\n",
    "l = length(xx_freq);\n",
    "array = zeros(xx_freq, 1);\n",
    "for n = 1:l\n",
    "    if(abs(xx_freq) <= 800)\n",
    "        array(n) = 1;\n",
    "    else\n",
    "        array(n) = 0;\n",
    "    end\n",
    "end\n",
    "error: out of memory or dimension too large for Octave's index type\n",
    "%}\n",
    "\n",
    "f_t = tr_fourier.*(abs(xx_freq) <= 800); % filter defined on demand\n",
    "restored = ifft(ifftshift(f_t));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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t9rfffvvee+99+OGHi4uLzWZza2sry7Isy1JKPSP9EwDgdGdf9r2zs1Mqlcrl8sLCQqVSSSllWba+vt5sNiuVytzc3N7eXvdIq9XqmTD6vQBg7J0dpM6XqTQajSzLGo1GsVhMKWVZVq/X8/HukUKh0DMBAM406GdI1Wr14cOHndLkg7Ozs/mNnpH+CQBwukGDtLa2tru7+/Dhw5RSs9nMBzsnQD0j/RN6fPTRR/3/YCUAl9nZQapUKnt7eyml6enplFKxWDw+Pk4pNZvNQqHQP9I/4UTd3/A6pH2BCzC1+vwC7w6T5OzPkG7fvr2ystJoNA4PD5eXl0ul0tbWVrVardfr+cdLPSP9EwDgTAN9l12r1To8POy+hrtWq/Vc0t0z0j+h20cfffTdd9/97MXDxZtafd5++MlF3R0myUDf9j09Pd1z9Xb/xdxnTgCAU/jqIABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkGIKp1ee/wF1gsgkSACEIEgAhCBIAIQgSACEIEgAhCBIAIQgSACEMGqRGo9FsNk+f0Gq13rQJAKd758wZrVZraWmpUCg0m81CobC2tnbjxo1CoZBSyjdTSouLi1mWHR4erq6uzs3N9WyOfCcAGH9nB2lnZ2d2djYPz6effrqwsFAoFJ48edKZsLe3l2XZ+vp6s9msVCqtVqt7U5AAGMTZQZqfn89v5G/BNZvN6enpSqXy7rvvLi8vT09PNxqNYrGYUsqyrF6vFwqF7s1RLh6AyXH2Z0hZlmVZVqvVlpaWlpeXW63W+++/XyqVrly5srKy0pmT35idne3fPNFUl5+7EwCMv7PPkFJK1Wr1hx9+ePToUV6aUqmUUpqbm9vb28sndK53yM+Qujff9JjtdvvnrBuACXP2GdL29nZ3jba2tmq1WveEYrF4fHycUsqveujZHM2yAZg0Z58h5Rd8Ly4u5purq6srKyvz8/OHh4e3b99OKZVKpa2trWq1Wq/Xy+Vyz+ZIVw/AxDg7SOvr6z0jz549q9VqCwsLnc+Kdnd3u0d6NgHgTAN9htSv/2LunhFXewNwLr46CIAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJRmJq9fkpm0C/QYPUaDSazWb3ZqvV6pnQPdI/AQBOcXaQWq3WrVu3tre3K5VKtVpNKS0uLm5vby8tLdVqtXxOz0j/BLg8TjkZcp4Ep3jnzBk7Ozuzs7Nra2sppU8//bRYLGZZtr6+3mw2K5XK3Nzc3t5e90ir1eqZMPq9AGDsnR2k+fn5/Eb+Flyj0SgWiymlLMvq9Xr/SKFQ6JkAAGc6+y27LMuyLKvVaktLS8vLy/lI/kezs7OdOd0j/RMA4HQDXdRQrVa3t7cfPXp0+/btlFLn6obOCVDPSP+EflNd3nbxAEyOs4O0vb39ww8/PHr0KD/vKRaLx8fHKaVms1koFPpH+iecqN1lWDsDwPg6+zOk/ILvxcXFfPPJkydbW1vVarVer5fL5ZRSqVTqHunZHOnqAZgYZwdpfX29Z2R3d7dWqy0sLHQ+K+oZ6Z8AAKc7O0gn6r+Yu2fE1d4AnIuvDgIgBEECIARBAiAEQQIgBEECIARBAiAEQQIgBEECIARBAiAEQQIgBEECIARBAiAEQQIgBEECIARBAiAEQQIgBEECIARBAiAEQQIgBEECIARBAiAEQQIgBEECIARBAiAEQQIgBEECIARBAiAEQQIgBEECIARBAiAEQQIgBEECIARBAiAEQQIgBEECIARBgrc0tfo87KPBOBIkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECTGwLj8pdEB1zlhuwPDIkgAhCBIAIQgSACEIEgAhCBIAIQgSACEIEgAhDBokFqtVrPZPGVCo9FotVpv2gSA070z4LydnZ0ff/xxbW0tpXTjxo1CoZBSKhQK+cji4mKWZYeHh6urq3Nzcz2bo1s9ABNjoCDdunXr8PDwq6++Sik1m81CofDkyZPOn+7t7WVZtr6+3mw2K5VKq9Xq3hQkAAYx0Ft2u7u7eY1SSs1mc3p6ulKpVKvV/E25RqNRLBZTSlmW1ev1ns2RrRyAiXLuixpardb7779fKpWuXLmysrKSD2ZZlt+YnZ3t3zzRVJdzrxqAiTPoZ0gdpVKpVCqllObm5vb29vLBzvUO9Xq9UCh0b77pcdrt9rkXC8DkOvcZ0tbWVq1W6x4pFovHx8fpp4+XejaHtVAAJtu5z5BmZ2dXVlbm5+cPDw9v376dUiqVSltbW9VqtV6vl8vlns0RrBmACTRokPLLu1NKxWLx2bNntVptYWGh81nR7u5u90jPJgCc6dxnSLn+i7l7RlztDcC5+OogAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhAkAEIQJABCECQAQhg0SK1Wq9lsdjYbjUar1eqe0DPSPwEATjFokHZ2dv70pz/ltxcXF7e3t5eWlmq12okj/RMA4HTvDDLp1q1bh4eHX331VUppb28vy7L19fVms1mpVObm5npGWq1Wz4QR7wIAk2CgM6Td3d28RimlRqNRLBZTSlmW1ev1/pH+CQBwpre5qCHLsvzG7OzsiSP9EwDgdG8TpM7VDZ0ToJ6R/gn9prq8xRoAmDDnDlKxWDw+Pk4pNZvNQqHQP9I/4UTtLm+/fAAmxUAXNXQrlUpbW1vVarVer5fL5f6R/gkAcKZBg7S2tta5vbu7W6vVFhYWOp8V9Yz0TwCA0537DCnXfzF3z4irvQE4F18dBEAIggRACIIEQAiCBEAIggRACIIEQAiCBEAIggRACIIEQAiCBEAIggRACIIEb2Nq9flFLwEmjSABEIIgARCCIAEQgiABEIIgARCCIAEQgiABEIIgARCCIAEQgiABEIIgARCCIAEQgiABEIIgARCCIAEQgiABEIIgARCCIAEQgiABEIIgwcWbWn1+0UuAiydIAIQgSACEIEgAhCBIAIQgSACEIEgAhCBIAIQgSACEIEgAhCBIAIQgSACEIEgAhCBIAIQgSACEIEgAhCBIAIQgSACEIEgAhCBIAIQgSACEMLQgNRqNVqv1pk0AON07b3GfGzduFAqFlFKhUFhbW0spLS4uZll2eHi4uro6NzfXsznkJQMwic4dpGazWSgUnjx50hnZ29vLsmx9fb3ZbFYqlVar1b0pSAAM4m2CND09XalU3n333eXl5enp6UajUSwWU0pZltXr9UKh0L05/CUDMInO/RlSq9V6//33S6XSlStXVlZW8sEsy/Ibs7Oz/Zsnmupy7lUDMHHOfYZUKpVKpVJKaW5ubm9vLx9sNpv5jfwMqXvzTY/TbrfPvVgAJte5z5C2trZqtVr3SLFYPD4+Tj99vNSzOayFAjDZzn2GNDs7u7KyMj8/f3h4ePv27ZRSqVTa2tqqVqv1er1cLvdsjmDNAEygcwepWCw+e/asVqstLCx0Piva3d3tHunZBIAzvc3fQ0op9V/M3TPiam8AzsVXBwEQgiABEIIgARCCIMH5TK0+H9MHh+AECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAmAEAQJgBAECYAQBAlOM7X6/JIvAH4xggRACIIEQAiCBEAIggRACIIEQAiCBEAIggRACIIEQAiCBEAIggRACIIEQAiCBEAIggRACIIEQAiCBEAIggRACIIEQAiCBP8l+L/QGnx58HMIEgAhCBIAIQgS/H9j9G7YGC0VBidIAIQgSNAr7PlH2IXBUAgSl84EH9YneNe4DAQJTtZ/cB/R4X6QJ1IaLgNBYpKdchw/1yH+QnowrBWKGeNCkGBcD9ljumx4k1EFqdFotFqtET34+JqamrroJVyMcdnx8x7iB5k/Lvs+dHb8EvqZ+z6SIC0uLm5vby8tLdVqtVE8PgzLBJxk9OzCBOwRl9bwg7S3t5dl2fr6+qNHjzY3N4f++PAm3cfi/ttDPFLHP+j37/KbbkMcww9So9EoFosppSzL6vX60B8f0vl705kzAcfioezC6cWCCzHVbreH+4jVavXjjz+em5tLKS0uLj558qR/zkcffTTcJwUggu++++6t7/vOENfR0Ww28xtvOkP65z//2b059Cj+Mvw/yl9A++EnndtTq8/bDz/p/PcCVzXZOj/kzoif9i+g+wc+vn7mRQ3DP0Pa29trNBpra2vNZnNlZWV3d3e4jw/ARBp+kFJKt27dmp2drdfr5XK5VCoN/fEBmDwjCVJKqVarZVmWZdkoHhyAyTOqIAHAuYzqmxpqtVr3NzX0f3FDz8iZE8ZFo9HoXNPRGfmZP4qx0Gq1Tt/x/pGJedFPMXl7lLvML3fP7/jl2fGeo3oawcHtf7755pvhLPYnrVbryy+/bLfb33777Xvvvffhhx8uLi42m82tra3Om3g9I2dOGO4KRyTf8f/85z9/+ctf/vWvf3388cfp/Hs6jjue++Mf//jixYt8r9NJr+BEvuinm7w96ricL3f/7/il2vHuo3oa0cGtPWybm5ubm5vtdvv4+Ph3v/vd3/72t9///vedzXa73TNy5oShr3BENjc3Hzx4kN/+5JNP2uff0zHd8Xa7/dvf/vZXv/pVZ/cvz4t+isnbo45L+3L3/I5fqh3vPqq3R3ZwG/7fQyqXy/mNRqORZVn/Fzf0jBQKhdMnDH2FIzI/P5/f6JyTnndP+yeMi93d3Wq12tm8PC/6KSZvjzou7cvd8zt+eXa856ieRnZwG9VnSNVq9eHDh50V5IOzs7P5jZ6RMyeMhfw8tFarLS0tLS8vdwbzGwPu6Tju+IkuyYt+usnboze5JC93/+/4JdnxXPdRPY3m4DacINVqtWq1ur293RlZW1vb3d19+PBhOumLG3pGzpwQWfe+5zcePXp0+/bt/E/Pu6djuuP9JvtFH9Dk7dGbXJ6Xu+d3/PLsePrvo3oazcFtOG/Zzc3N5V9el1KqVCpzc3OlUml6ejqlVCwWG41GvppCodA/cuaEoaxwdDr7vr29/cMPPzx69KjzR+fd0zHd8X4T/6IPYvL26E0uz8vd8zt+eXa856ieRnZwG/7fQ2o0GisrK/Pz84eHhx9//HG5XO7/4oaekTMnDHeFI1KpVA4PD9999918M/9W2fPu6TjueC7/UGFtbS3fvCQv+ukmb486LufL3f87fkl2vP+onkZ0cBvFJRk//vjj3//+9+Pj485Iz2b/yJkTxtfP/1GMqcv8ondM3h69yaV9uS/Jjvcf1dsjOLj5pgYAQhjVVXYAcC6CBEAIggRACIIEQAiCBEAI/wcLm1ide3QULgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure\n",
    "plot(xx_freq, abs(tr_fourier)); \n",
    "title(\"Spettro delle frequenze\");\n",
    "box off"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "error: 'f_t' undefined near line 1 column 19\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure\n",
    "plot(xx_freq, abs(f_t));\n",
    "title(\"Spettro delle frequenze con filtro passa basso\");\n",
    "box off"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "error: 'restored' undefined near line 1 column 15\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure\n",
    "plot(xx, real(restored));\n",
    "title(\"Segnale audio ricostruito\");\n",
    "box off"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "% riproduzione audio originale\n",
    "%sound(f, fs); \n",
    "\n",
    "% riproduzione audio corrotto\n",
    "%sound(fp, fs);\n",
    "\n",
    "% riproduzione audio ripulito\n",
    "%sound(real(restored), fs);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Esercizio 4\n",
    "\n",
    "A partire dall'immagine `cameraman.png` fornita, si implementi un filtro passa basso e un filtro passa alto di dimensione variabile per effettuare il filtraggio dell'immagine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "im = imread(\"resources/cameraman.png\"); % immagine come matrice di uint8\n",
    "\n",
    "figure\n",
    "imshow(im);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dimensione immagine 256 x 256\n"
     ]
    }
   ],
   "source": [
    "im = double(im); % cast a double richiesto per l'elaborazione (im(:,:,1))\n",
    "\n",
    "[w,h] = size(im);\n",
    "fprintf(\"Dimensione immagine %d x %d\\n\",w, h);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trasf = fftshift(fft2(im));\n",
    "figure\n",
    "imshow((log(1 + abs(trasf))), []); % si aggiunge 1 per evitare logaritmi nulli\n",
    "title(\"Spettro dell'immagine\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "% calcolo centro dell'immagine\n",
    "yc = floor(w / 2) + 1;\n",
    "xc = floor(h / 2) + 1;\n",
    "\n",
    "raggio = input(\n",
    "    \"Raggio del filtro (positivo e minore della dimensione dell'immagine fratto due)\");\n",
    "\n",
    "% inizializzazione del filtro passa basso\n",
    "filtro_PB = ones(w,h);\n",
    "\n",
    "for m=1:w\n",
    "   for l=1:h\n",
    "       % calcolo distanza del punto (m,l) della matrice dal centro\n",
    "       d = sqrt((xc - l).^2 + (yc - m).^2);\n",
    "\n",
    "       % tutti i punti esterni al cerchio non formano il filtro e vanno\n",
    "       % inizializzati a zero\n",
    "       if d > raggio\n",
    "           filtro_PB(m,l) = 0;\n",
    "       end\n",
    "   end\n",
    "end\n",
    "\n",
    "figure\n",
    "imshow(filtro_PB)\n",
    "title('Filtro passa basso')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%{\n",
    "Si annullano nella trasformata di Fourier dell'immagine tutte le frequenze che\n",
    "stanno fuori dal cerchio, facendo una moltiplicazione point-wise tra i\n",
    "valori della trasformata di Fourier ed il filtro_PB;\n",
    "%}\n",
    "           \n",
    "trasf_PB = trasf.* filtro_PB;\n",
    "\n",
    "% Si calcola la trasformata di Fourier inversa a partire \n",
    "% dalla trasformata di Fourier filtrata con il filtro passa basso             \n",
    "\n",
    "Im_PB = ifft2( ifftshift(trasf_PB) );\n",
    "\n",
    "figure\n",
    "imshow(abs(Im_PB),[])\n",
    "title('Applicazione del filtro passa basso')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "% il filtro passa alto è l'inverso del passa basso\n",
    "filtro_PH = 1 - filtro_PB;\n",
    "figure\n",
    "imshow(filtro_PH)\n",
    "title(\"Filtro Passa Alto\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%{\n",
    "Si annullano nella trasformata di Fourier dell'immagine tutte le\n",
    "frequenze basse che stanno dentro il cerchio, facendo una\n",
    "moltiplicazione point-wise tra i valori della trasformata di\n",
    "Fourier ed il filtro_PH \n",
    "%}\n",
    "\n",
    "trasf_PH=trasf.*filtro_PH;\n",
    "Im_PH=ifft2(ifftshift(trasf_PH));\n",
    "figure\n",
    "imshow(abs(Im_PH),[])\n",
    "title(\"Immagine filtrata con il filtro passa alto\")"
   ]
  }
 ],
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    {
     "text": "GNU Octave",
     "url": "https://www.gnu.org/software/octave/support.html"
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    {
     "text": "Octave Kernel",
     "url": "https://github.com/Calysto/octave_kernel"
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    {
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